Comparison of predictive equations for resting energy expenditure in severely obese Caucasian children and adolescents

The objectives of the present study were to develop and cross-validate new equations for predicting resting energy expenditure (REE) in severely obese children and adolescents, and to determine the accuracy of new equations using the Bland–Altman method. The subjects of the study were 574 obese Caucasian children and adolescents (mean BMI z-score 3·3). REE was determined by indirect calorimetry and body composition by bioelectrical impedance analysis. Equations were derived by stepwise multiple regression analysis using a calibration cohort of 287 subjects and the equations were cross-validated in the remaining 287 subjects. Two new specific equations based on anthropometric parameters were generated as follows: (1) REE=(Sex×892·68)−(Age×115·93)+(Weight×54·96)+(Stature×1816·23)+1484·50 (R2 0·66; se 1028·97 kJ); (2) REE=(Sex×909·12)−(Age×107·48)+(fat-free mass×68·39)+(fat mass×55·19)+3631·23 (R2 0·66; se 1034·28 kJ). In the cross-validation group, mean predicted REE values were not significantly different from the mean measured REE for all children and adolescents, as well as for boys and for girls (difference <2 %) and the limits of agreement (±2 sd) were +2·06 and −1·77 MJ/d (NS). The new prediction equations allow an accurate estimation of REE in groups of severely obese children and adolescents. These equations might be useful for health care professionals and researchers when estimating REE in severely obese children and adolescents.

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Accuracy of the Common Predictive Equations for Estimating Resting Energy Expenditure among Normal and Overweight Girl University Students

Journal of the American College of Nutrition ◽

10.1080/07315724.2014.938280 ◽

2015 ◽

Vol 35 (2) ◽

pp. 136-142 ◽

Cited By ~ 3

Author(s):

Nazli Namazi ◽

Soghra Aliasgharzadeh ◽

Reza Mahdavi ◽

Fariba Kolahdooz

Keyword(s):

Energy Expenditure ◽

University Students ◽

Resting Energy Expenditure ◽

Predictive Equations ◽

The Common ◽

Resting Energy

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Reliability of resting energy expenditure in major burns: Comparison between measured and predictive equations

Clinical Nutrition ◽

10.1016/j.clnu.2018.12.003 ◽

2019 ◽

Vol 38 (6) ◽

pp. 2763-2769 ◽

Cited By ~ 5

Author(s):

Jinwoo Jeon ◽

Dohern Kym ◽

Yong Suk Cho ◽

Youngmin Kim ◽

Jaechul Yoon ◽

...

Keyword(s):

Energy Expenditure ◽

Resting Energy Expenditure ◽

Predictive Equations ◽

Resting Energy

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Resting energy expenditure in elite athletes: development of new predictive equations based on anthropometric variables and bioelectrical impedance analysis derived phase angle

Journal of the International Society of Sports Nutrition ◽

10.1186/s12970-021-00465-x ◽

2021 ◽

Vol 18 (1) ◽

Author(s):

Maurizio Marra ◽

Olivia Di Vincenzo ◽

Iolanda Cioffi ◽

Rosa Sammarco ◽

Delia Morlino ◽

...

Keyword(s):

Energy Expenditure ◽

Phase Angle ◽

Elite Athletes ◽

Resting Energy Expenditure ◽

Sport Performance ◽

Accurate Estimation ◽

Anthropometric Parameters ◽

Predictive Equations ◽

Good Prediction Accuracy ◽

Resting Energy

Abstract Background An accurate estimation of athletes’ energy needs is crucial in diet planning to improve sport performance and to maintain an appropriate body composition. This study aimed to develop and validate in elite athletes new equations for estimating resting energy expenditure (REE) based on anthropometric parameters as well as bioimpedance analysis (BIA)-derived raw variables and to validate the accuracy of selected predictive equations. Methods Adult elite athletes aged 18–40 yrs were studied. Anthropometry, indirect calorimetry and BIA were performed in all subjects. The new predictive equations were generated using different regression models. The accuracy of the new equations was assessed at the group level (bias) and at the individual level (precision accuracy), and then compared with the one of five equations used in the general population or three athletes-specific formulas. Results One-hundred and twenty-six male athletes (age 26.9 ± 9.1 yrs; weight 71.3 ± 10.9 kg; BMI 22.8 ± 2.7 kg/m2) from different sport specialties were randomly assigned to the calibration (n = 75) or validation group (n = 51). REE was directly correlated with individual characteristics, except for age, and raw BIA variables. Most of the equations from the literature were reasonably accurate at the population level (bias within ±5%). The new equations showed a mean bias −0.3% (Eq. A based on anthropometric parameters) and −0.6% (Eq. B based on BIA-derived raw variables). Precision accuracy (individual predicted-measured differences within ±5%) was ~75% in six out of eight of the selected equations and even higher for Eq. A (82.4%) and Eq. B (92.2%). Conclusion In elite athletes, BIA-derived phase angle is a significant predictor of REE. The new equations have a very good prediction accuracy at both group and individual levels. The use of phase angle as predictor of REE requires further research with respect to different sport specialties, training programs and training level.

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Accuracy and Validity of Resting Energy Expenditure Predictive Equations in Middle-Aged Adults

Nutrients ◽

10.3390/nu10111635 ◽

2018 ◽

Vol 10 (11) ◽

pp. 1635 ◽

Cited By ~ 12

Author(s):

Francisco Amaro-Gahete ◽

Lucas Jurado-Fasoli ◽

Alejandro De-la-O ◽

Ángel Gutierrez ◽

Manuel Castillo ◽

...

Keyword(s):

Energy Expenditure ◽

Indirect Calorimetry ◽

Prediction Accuracy ◽

Weight Status ◽

Resting Energy Expenditure ◽

Normal Weight ◽

Middle Aged ◽

Predictive Equations ◽

Middle Aged Adults ◽

Resting Energy

Indirect calorimetry (IC) is considered the reference method to determine the resting energy expenditure (REE), but its use in a clinical context is limited. Alternatively, there is a number of REE predictive equations to estimate the REE. However, it has been shown that the available REE predictive equations could either overestimate or underestimate the REE as measured by IC. Moreover, the role of the weight status in the accuracy and validity of the REE predictive equations requires further attention. Therefore, this study aimed to determine the accuracy and validity of REE predictive equations in normal-weight, overweight, and obese sedentary middle-aged adults. A total of 73 sedentary middle-aged adults (53% women, 40–65 years old) participated in the study. We measured REE by indirect calorimetry, strictly following the standard procedures, and we compared it with the values obtained from 33 predictive equations. The most accurate predictive equations in middle-aged sedentary adults were: (i) the equation of FAO/WHO/UNU in normal-weight individuals (50.0% of prediction accuracy), (ii) the equation of Livingston in overweight individuals (46.9% of prediction accuracy), and (iii) the equation of Owen in individuals with obesity (52.9% of prediction accuracy). Our study shows that the weight status plays an important role in the accuracy and validity of different REE predictive equations in middle-aged adults.

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